Dataset statistics
| Number of variables | 27 |
|---|---|
| Number of observations | 723 |
| Missing cells | 237 |
| Missing cells (%) | 1.2% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 152.6 KiB |
| Average record size in memory | 216.2 B |
Variable types
| NUM | 13 |
|---|---|
| CAT | 11 |
| UNSUPPORTED | 2 |
| URL | 1 |
Reproduction
| Analysis started | 2020-11-23 10:12:40.834982 |
|---|---|
| Analysis finished | 2020-11-23 10:13:53.623056 |
| Duration | 1 minute and 12.79 seconds |
| Version | pandas-profiling v2.8.0 |
| Command line | pandas_profiling --config_file config.yaml [YOUR_FILE.csv] |
| Download configuration | config.yaml |
director has a high cardinality: 585 distinct values | High cardinality |
released has a high cardinality: 308 distinct values | High cardinality |
star has a high cardinality: 437 distinct values | High cardinality |
writer has a high cardinality: 613 distinct values | High cardinality |
hashtag has a high cardinality: 722 distinct values | High cardinality |
name_roten has a high cardinality: 722 distinct values | High cardinality |
synopsis has a high cardinality: 661 distinct values | High cardinality |
year is highly correlated with year_released | High correlation |
year_released is highly correlated with year | High correlation |
calificacion1_dec is highly correlated with calificacion1 | High correlation |
calificacion1 is highly correlated with calificacion1_dec | High correlation |
calificacion2_dec is highly correlated with calificacion2 | High correlation |
calificacion2 is highly correlated with calificacion2_dec | High correlation |
calificacion1 has 58 (8.0%) missing values | Missing |
calificacion2 has 58 (8.0%) missing values | Missing |
calificacion1_dec has 58 (8.0%) missing values | Missing |
calificacion2_dec has 58 (8.0%) missing values | Missing |
director is uniformly distributed | Uniform |
star is uniformly distributed | Uniform |
writer is uniformly distributed | Uniform |
hashtag is uniformly distributed | Uniform |
name_roten is uniformly distributed | Uniform |
gross has unique values | Unique |
company is an unsupported type, check if it needs cleaning or further analysis | Unsupported |
name is an unsupported type, check if it needs cleaning or further analysis | Unsupported |
budget has 124 (17.2%) zeros | Zeros |
promedio_ganancia has 292 (40.4%) zeros | Zeros |
calificacion1_dec has 26 (3.6%) zeros | Zeros |
| Distinct count | 141 |
|---|---|
| Unique (%) | 19.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 40008846.70401107 |
|---|---|
| Minimum | 0 |
| Maximum | 250000000 |
| Zeros | 124 |
| Zeros (%) | 17.2% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 4450000 |
| median | 20000000 |
| Q3 | 50000000 |
| 95-th percentile | 170000000 |
| Maximum | 250000000 |
| Range | 250000000 |
| Interquartile range (IQR) | 45550000 |
Descriptive statistics
| Standard deviation | 52935707.8 |
|---|---|
| Coefficient of variation (CV) | 1.323100068 |
| Kurtosis | 2.813575462 |
| Mean | 40008846.7 |
| Median Absolute Deviation (MAD) | 19000000 |
| Skewness | 1.840083157 |
| Sum | 2.892639617e+10 |
| Variance | 2.80218916e+15 |
| Value | Count | Frequency (%) | |
| 0 | 124 | 17.2% | |
| 20000000 | 26 | 3.6% | |
| 5000000 | 24 | 3.3% | |
| 40000000 | 23 | 3.2% | |
| 30000000 | 22 | 3.0% | |
| 35000000 | 22 | 3.0% | |
| 15000000 | 20 | 2.8% | |
| 25000000 | 19 | 2.6% | |
| 10000000 | 19 | 2.6% | |
| 50000000 | 16 | 2.2% | |
| Other values (131) | 408 | 56.4% |
| Value | Count | Frequency (%) | |
| 0 | 124 | 17.2% | |
| 50000 | 2 | 0.3% | |
| 100000 | 2 | 0.3% | |
| 130000 | 1 | 0.1% | |
| 200000 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 250000000 | 3 | 0.4% | |
| 245000000 | 2 | 0.3% | |
| 225000000 | 2 | 0.3% | |
| 215000000 | 2 | 0.3% | |
| 210000000 | 1 | 0.1% |
country
Categorical
| Distinct count | 3 |
|---|---|
| Unique (%) | 0.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| USA | |
|---|---|
| UK | |
| France | 30 |
| Value | Count | Frequency (%) | |
| USA | 577 | 79.8% | |
| UK | 116 | 16.0% | |
| France | 30 | 4.1% |
Length
| Max length | 6 |
|---|---|
| Median length | 3 |
| Mean length | 2.964038728 |
| Min length | 2 |
| Distinct count | 585 |
|---|---|
| Unique (%) | 80.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| Woody Allen | 4 |
|---|---|
| Denis Villeneuve | 3 |
| James DeMonaco | 3 |
| Ridley Scott | 3 |
| Clint Eastwood | 3 |
| Other values (580) |
| Value | Count | Frequency (%) | |
| Woody Allen | 4 | 0.6% | |
| Denis Villeneuve | 3 | 0.4% | |
| James DeMonaco | 3 | 0.4% | |
| Ridley Scott | 3 | 0.4% | |
| Clint Eastwood | 3 | 0.4% | |
| Shawn Levy | 3 | 0.4% | |
| Robert Schwentke | 3 | 0.4% | |
| Paul Feig | 3 | 0.4% | |
| James Wan | 3 | 0.4% | |
| Nicholas Stoller | 3 | 0.4% | |
| Other values (575) | 692 | 95.7% |
Length
| Max length | 27 |
|---|---|
| Median length | 13 |
| Mean length | 12.99585062 |
| Min length | 3 |
genre
Categorical
| Distinct count | 14 |
|---|---|
| Unique (%) | 1.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| Action | |
|---|---|
| Comedy | |
| Drama | |
| Biography | |
| Adventure | |
| Other values (9) |
| Value | Count | Frequency (%) | |
| Action | 175 | 24.2% | |
| Comedy | 162 | 22.4% | |
| Drama | 144 | 19.9% | |
| Biography | 68 | 9.4% | |
| Adventure | 46 | 6.4% | |
| Crime | 44 | 6.1% | |
| Animation | 42 | 5.8% | |
| Horror | 33 | 4.6% | |
| Mystery | 3 | 0.4% | |
| Sci-Fi | 2 | 0.3% | |
| Other values (4) | 4 | 0.6% |
Length
| Max length | 9 |
|---|---|
| Median length | 6 |
| Mean length | 6.398340249 |
| Min length | 5 |
| Distinct count | 723 |
|---|---|
| Unique (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 53309893.669432916 |
|---|---|
| Minimum | 441 |
| Maximum | 936662225 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 441 |
|---|---|
| 5-th percentile | 27778.5 |
| Q1 | 2233985.5 |
| median | 22525921 |
| Q3 | 65184892.5 |
| 95-th percentile | 227843079.5 |
| Maximum | 936662225 |
| Range | 936661784 |
| Interquartile range (IQR) | 62950907 |
Descriptive statistics
| Standard deviation | 87040912.25 |
|---|---|
| Coefficient of variation (CV) | 1.632734681 |
| Kurtosis | 22.08329029 |
| Mean | 53309893.67 |
| Median Absolute Deviation (MAD) | 22105655 |
| Skewness | 3.74713064 |
| Sum | 3.854305312e+10 |
| Variance | 7.576120405e+15 |
| Value | Count | Frequency (%) | |
| 233921534 | 1 | 0.1% | |
| 461162 | 1 | 0.1% | |
| 23049575 | 1 | 0.1% | |
| 37047 | 1 | 0.1% | |
| 16740 | 1 | 0.1% | |
| 42652003 | 1 | 0.1% | |
| 44469602 | 1 | 0.1% | |
| 130178411 | 1 | 0.1% | |
| 32095 | 1 | 0.1% | |
| 116400 | 1 | 0.1% | |
| Other values (713) | 713 | 98.6% |
| Value | Count | Frequency (%) | |
| 441 | 1 | 0.1% | |
| 2137 | 1 | 0.1% | |
| 2254 | 1 | 0.1% | |
| 4105 | 1 | 0.1% | |
| 4267 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 936662225 | 1 | 0.1% | |
| 652270625 | 1 | 0.1% | |
| 532177324 | 1 | 0.1% | |
| 486295561 | 1 | 0.1% | |
| 459005868 | 1 | 0.1% |
rating
Categorical
| Distinct count | 8 |
|---|---|
| Unique (%) | 1.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| R | |
|---|---|
| PG-13 | |
| PG | |
| NOT RATED | 17 |
| UNRATED | 5 |
| Other values (3) | 5 |
| Value | Count | Frequency (%) | |
| R | 355 | 49.1% | |
| PG-13 | 267 | 36.9% | |
| PG | 74 | 10.2% | |
| NOT RATED | 17 | 2.4% | |
| UNRATED | 5 | 0.7% | |
| G | 3 | 0.4% | |
| Not specified | 1 | 0.1% | |
| NC-17 | 1 | 0.1% |
Length
| Max length | 13 |
|---|---|
| Median length | 2 |
| Mean length | 2.831258645 |
| Min length | 1 |
day_released
Real number (ℝ≥0)
| Distinct count | 31 |
|---|---|
| Unique (%) | 4.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 16.172890733056708 |
|---|---|
| Minimum | 1 |
| Maximum | 31 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 2 |
| Q1 | 9 |
| median | 17 |
| Q3 | 23 |
| 95-th percentile | 29 |
| Maximum | 31 |
| Range | 30 |
| Interquartile range (IQR) | 14 |
Descriptive statistics
| Standard deviation | 8.365059624 |
|---|---|
| Coefficient of variation (CV) | 0.5172272392 |
| Kurtosis | -1.127788383 |
| Mean | 16.17289073 |
| Median Absolute Deviation (MAD) | 7 |
| Skewness | -0.1388383412 |
| Sum | 11693 |
| Variance | 69.97422252 |
| Value | Count | Frequency (%) | |
| 25 | 48 | 6.6% | |
| 23 | 32 | 4.4% | |
| 18 | 31 | 4.3% | |
| 26 | 30 | 4.1% | |
| 16 | 29 | 4.0% | |
| 11 | 28 | 3.9% | |
| 19 | 28 | 3.9% | |
| 21 | 27 | 3.7% | |
| 10 | 26 | 3.6% | |
| 20 | 26 | 3.6% | |
| Other values (21) | 418 | 57.8% |
| Value | Count | Frequency (%) | |
| 1 | 24 | 3.3% | |
| 2 | 17 | 2.4% | |
| 3 | 16 | 2.2% | |
| 4 | 21 | 2.9% | |
| 5 | 19 | 2.6% |
| Value | Count | Frequency (%) | |
| 31 | 9 | 1.2% | |
| 30 | 12 | 1.7% | |
| 29 | 18 | 2.5% | |
| 28 | 16 | 2.2% | |
| 27 | 25 | 3.5% |
month_released
Real number (ℝ≥0)
| Distinct count | 12 |
|---|---|
| Unique (%) | 1.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 6.643153526970955 |
|---|---|
| Minimum | 1 |
| Maximum | 12 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 4 |
| median | 7 |
| Q3 | 10 |
| 95-th percentile | 12 |
| Maximum | 12 |
| Range | 11 |
| Interquartile range (IQR) | 6 |
Descriptive statistics
| Standard deviation | 3.417798778 |
|---|---|
| Coefficient of variation (CV) | 0.5144843883 |
| Kurtosis | -1.190246935 |
| Mean | 6.643153527 |
| Median Absolute Deviation (MAD) | 3 |
| Skewness | -0.1028426151 |
| Sum | 4803 |
| Variance | 11.68134849 |
| Value | Count | Frequency (%) | |
| 8 | 78 | 10.8% | |
| 10 | 66 | 9.1% | |
| 4 | 65 | 9.0% | |
| 11 | 64 | 8.9% | |
| 9 | 63 | 8.7% | |
| 7 | 63 | 8.7% | |
| 1 | 61 | 8.4% | |
| 12 | 55 | 7.6% | |
| 3 | 54 | 7.5% | |
| 5 | 52 | 7.2% | |
| Other values (2) | 102 | 14.1% |
| Value | Count | Frequency (%) | |
| 1 | 61 | 8.4% | |
| 2 | 52 | 7.2% | |
| 3 | 54 | 7.5% | |
| 4 | 65 | 9.0% | |
| 5 | 52 | 7.2% |
| Value | Count | Frequency (%) | |
| 12 | 55 | 7.6% | |
| 11 | 64 | 8.9% | |
| 10 | 66 | 9.1% | |
| 9 | 63 | 8.7% | |
| 8 | 78 | 10.8% |
| Distinct count | 5 |
|---|---|
| Unique (%) | 0.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2014.6929460580914 |
|---|---|
| Minimum | 2013 |
| Maximum | 2017 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 2013 |
|---|---|
| 5-th percentile | 2013 |
| Q1 | 2014 |
| median | 2015 |
| Q3 | 2016 |
| 95-th percentile | 2017 |
| Maximum | 2017 |
| Range | 4 |
| Interquartile range (IQR) | 2 |
Descriptive statistics
| Standard deviation | 1.195463508 |
|---|---|
| Coefficient of variation (CV) | 0.0005933725584 |
| Kurtosis | -1.04928311 |
| Mean | 2014.692946 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | 0.07756779823 |
| Sum | 1456623 |
| Variance | 1.429132998 |
| Value | Count | Frequency (%) | |
| 2015 | 184 | 25.4% | |
| 2014 | 178 | 24.6% | |
| 2016 | 174 | 24.1% | |
| 2013 | 148 | 20.5% | |
| 2017 | 39 | 5.4% |
| Value | Count | Frequency (%) | |
| 2013 | 148 | 20.5% | |
| 2014 | 178 | 24.6% | |
| 2015 | 184 | 25.4% | |
| 2016 | 174 | 24.1% | |
| 2017 | 39 | 5.4% |
| Value | Count | Frequency (%) | |
| 2017 | 39 | 5.4% | |
| 2016 | 174 | 24.1% | |
| 2015 | 184 | 25.4% | |
| 2014 | 178 | 24.6% | |
| 2013 | 148 | 20.5% |
| Distinct count | 308 |
|---|---|
| Unique (%) | 42.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| 2015-01-23 | 7 |
|---|---|
| 2016-11-18 | 7 |
| 2015-09-25 | 7 |
| 2016-03-4 | 6 |
| 2015-08-7 | 6 |
| Other values (303) |
| Value | Count | Frequency (%) | |
| 2015-01-23 | 7 | 1.0% | |
| 2016-11-18 | 7 | 1.0% | |
| 2015-09-25 | 7 | 1.0% | |
| 2016-03-4 | 6 | 0.8% | |
| 2015-08-7 | 6 | 0.8% | |
| 2016-08-26 | 6 | 0.8% | |
| 2015-01-16 | 6 | 0.8% | |
| 2014-08-8 | 6 | 0.8% | |
| 2016-10-21 | 6 | 0.8% | |
| 2015-04-10 | 6 | 0.8% | |
| Other values (298) | 660 | 91.3% |
Length
| Max length | 10 |
|---|---|
| Median length | 10 |
| Mean length | 9.742738589 |
| Min length | 9 |
runtime
Real number (ℝ≥0)
| Distinct count | 78 |
|---|---|
| Unique (%) | 10.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 108.4508990318119 |
|---|---|
| Minimum | 76 |
| Maximum | 180 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 76 |
|---|---|
| 5-th percentile | 88 |
| Q1 | 97 |
| median | 106 |
| Q3 | 118 |
| 95-th percentile | 137 |
| Maximum | 180 |
| Range | 104 |
| Interquartile range (IQR) | 21 |
Descriptive statistics
| Standard deviation | 15.9554004 |
|---|---|
| Coefficient of variation (CV) | 0.1471209602 |
| Kurtosis | 1.573109862 |
| Mean | 108.450899 |
| Median Absolute Deviation (MAD) | 10 |
| Skewness | 0.9896742011 |
| Sum | 78410 |
| Variance | 254.5748018 |
| Value | Count | Frequency (%) | |
| 100 | 31 | 4.3% | |
| 98 | 26 | 3.6% | |
| 106 | 25 | 3.5% | |
| 104 | 21 | 2.9% | |
| 99 | 20 | 2.8% | |
| 91 | 20 | 2.8% | |
| 101 | 20 | 2.8% | |
| 97 | 20 | 2.8% | |
| 96 | 20 | 2.8% | |
| 95 | 19 | 2.6% | |
| Other values (68) | 501 | 69.3% |
| Value | Count | Frequency (%) | |
| 76 | 2 | 0.3% | |
| 77 | 1 | 0.1% | |
| 79 | 2 | 0.3% | |
| 80 | 1 | 0.1% | |
| 81 | 2 | 0.3% |
| Value | Count | Frequency (%) | |
| 180 | 2 | 0.3% | |
| 169 | 1 | 0.1% | |
| 167 | 1 | 0.1% | |
| 165 | 2 | 0.3% | |
| 163 | 1 | 0.1% |
score
Real number (ℝ≥0)
| Distinct count | 47 |
|---|---|
| Unique (%) | 6.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 6.478423236514524 |
|---|---|
| Minimum | 1.5 |
| Maximum | 8.6 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 1.5 |
|---|---|
| 5-th percentile | 5.1 |
| Q1 | 6 |
| median | 6.5 |
| Q3 | 7.1 |
| 95-th percentile | 7.8 |
| Maximum | 8.6 |
| Range | 7.1 |
| Interquartile range (IQR) | 1.1 |
Descriptive statistics
| Standard deviation | 0.8473221649 |
|---|---|
| Coefficient of variation (CV) | 0.1307914185 |
| Kurtosis | 1.751003128 |
| Mean | 6.478423237 |
| Median Absolute Deviation (MAD) | 0.5 |
| Skewness | -0.5803962431 |
| Sum | 4683.9 |
| Variance | 0.7179548511 |
| Value | Count | Frequency (%) | |
| 6.3 | 47 | 6.5% | |
| 6.5 | 42 | 5.8% | |
| 6.7 | 42 | 5.8% | |
| 6.2 | 38 | 5.3% | |
| 7 | 35 | 4.8% | |
| 6.6 | 33 | 4.6% | |
| 6.4 | 32 | 4.4% | |
| 5.7 | 31 | 4.3% | |
| 7.1 | 29 | 4.0% | |
| 6 | 27 | 3.7% | |
| Other values (37) | 367 | 50.8% |
| Value | Count | Frequency (%) | |
| 1.5 | 1 | 0.1% | |
| 3.1 | 1 | 0.1% | |
| 3.5 | 1 | 0.1% | |
| 3.9 | 2 | 0.3% | |
| 4.1 | 2 | 0.3% |
| Value | Count | Frequency (%) | |
| 8.6 | 1 | 0.1% | |
| 8.5 | 1 | 0.1% | |
| 8.2 | 3 | 0.4% | |
| 8.1 | 9 | 1.2% | |
| 8 | 9 | 1.2% |
| Distinct count | 437 |
|---|---|
| Unique (%) | 60.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| Robert De Niro | 8 |
|---|---|
| Miles Teller | 6 |
| Michael Fassbender | 6 |
| Jesse Eisenberg | 6 |
| Mark Wahlberg | 6 |
| Other values (432) |
| Value | Count | Frequency (%) | |
| Robert De Niro | 8 | 1.1% | |
| Miles Teller | 6 | 0.8% | |
| Michael Fassbender | 6 | 0.8% | |
| Jesse Eisenberg | 6 | 0.8% | |
| Mark Wahlberg | 6 | 0.8% | |
| Jason Bateman | 6 | 0.8% | |
| Matthew McConaughey | 6 | 0.8% | |
| Jennifer Lawrence | 5 | 0.7% | |
| Christian Bale | 5 | 0.7% | |
| Steve Carell | 5 | 0.7% | |
| Other values (427) | 664 | 91.8% |
Length
| Max length | 23 |
|---|---|
| Median length | 13 |
| Mean length | 13.19502075 |
| Min length | 8 |
votes
Real number (ℝ≥0)
| Distinct count | 722 |
|---|---|
| Unique (%) | 99.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 104574.38865836791 |
|---|---|
| Minimum | 980 |
| Maximum | 1095553 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 980 |
|---|---|
| 5-th percentile | 6288.1 |
| Q1 | 23162.5 |
| median | 56365 |
| Q3 | 122419 |
| 95-th percentile | 388218.1 |
| Maximum | 1095553 |
| Range | 1094573 |
| Interquartile range (IQR) | 99256.5 |
Descriptive statistics
| Standard deviation | 134459.103 |
|---|---|
| Coefficient of variation (CV) | 1.285774698 |
| Kurtosis | 9.047139369 |
| Mean | 104574.3887 |
| Median Absolute Deviation (MAD) | 40249 |
| Skewness | 2.628903852 |
| Sum | 75607283 |
| Variance | 1.807925039e+10 |
| Value | Count | Frequency (%) | |
| 9141 | 2 | 0.3% | |
| 105471 | 1 | 0.1% | |
| 31057 | 1 | 0.1% | |
| 72027 | 1 | 0.1% | |
| 8538 | 1 | 0.1% | |
| 341715 | 1 | 0.1% | |
| 33542 | 1 | 0.1% | |
| 13654 | 1 | 0.1% | |
| 13653 | 1 | 0.1% | |
| 59906 | 1 | 0.1% | |
| Other values (712) | 712 | 98.5% |
| Value | Count | Frequency (%) | |
| 980 | 1 | 0.1% | |
| 1248 | 1 | 0.1% | |
| 1645 | 1 | 0.1% | |
| 1896 | 1 | 0.1% | |
| 1959 | 1 | 0.1% |
| Value | Count | Frequency (%) | |
| 1095553 | 1 | 0.1% | |
| 895552 | 1 | 0.1% | |
| 791340 | 1 | 0.1% | |
| 687192 | 1 | 0.1% | |
| 668625 | 1 | 0.1% |
| Distinct count | 613 |
|---|---|
| Unique (%) | 84.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| Steven Knight | 6 |
|---|---|
| Woody Allen | 4 |
| Luc Besson | 4 |
| Skip Woods | 3 |
| Darren Lemke | 3 |
| Other values (608) |
| Value | Count | Frequency (%) | |
| Steven Knight | 6 | 0.8% | |
| Woody Allen | 4 | 0.6% | |
| Luc Besson | 4 | 0.6% | |
| Skip Woods | 3 | 0.4% | |
| Darren Lemke | 3 | 0.4% | |
| Scott Neustadter | 3 | 0.4% | |
| Joel Coen | 3 | 0.4% | |
| Peter Landesman | 3 | 0.4% | |
| Christopher Markus | 3 | 0.4% | |
| Andrew Jay Cohen | 3 | 0.4% | |
| Other values (603) | 688 | 95.2% |
Length
| Max length | 27 |
|---|---|
| Median length | 13 |
| Mean length | 13.02904564 |
| Min length | 7 |
| Distinct count | 4 |
|---|---|
| Unique (%) | 0.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| 2014 | |
|---|---|
| 2013 | |
| 2016 | |
| 2015 |
| Value | Count | Frequency (%) | |
| 2014 | 185 | 25.6% | |
| 2013 | 185 | 25.6% | |
| 2016 | 182 | 25.2% | |
| 2015 | 171 | 23.7% |
Length
| Max length | 4 |
|---|---|
| Median length | 4 |
| Mean length | 4 |
| Min length | 4 |
| Distinct count | 722 |
|---|---|
| Unique (%) | 99.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| #Concussion | 2 |
|---|---|
| #Stoker | 1 |
| #TheBFG | 1 |
| #Don'tBreathe | 1 |
| #Dope | 1 |
| Other values (717) |
| Value | Count | Frequency (%) | |
| #Concussion | 2 | 0.3% | |
| #Stoker | 1 | 0.1% | |
| #TheBFG | 1 | 0.1% | |
| #Don'tBreathe | 1 | 0.1% | |
| #Dope | 1 | 0.1% | |
| #ALongWayDown | 1 | 0.1% | |
| #Riddick | 1 | 0.1% | |
| #ExMachina | 1 | 0.1% | |
| #TheHollars | 1 | 0.1% | |
| #300:RiseofanEmpire | 1 | 0.1% | |
| Other values (712) | 712 | 98.5% |
Length
| Max length | 51 |
|---|---|
| Median length | 13 |
| Mean length | 13.91286307 |
| Min length | 3 |
| Distinct count | 722 |
|---|---|
| Unique (%) | 99.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| concussion | 2 |
|---|---|
| kubo_and_the_two_strings | 1 |
| mr._peabody_&_sherman | 1 |
| pawn_sacrifice | 1 |
| turbo | 1 |
| Other values (717) |
| Value | Count | Frequency (%) | |
| concussion | 2 | 0.3% | |
| kubo_and_the_two_strings | 1 | 0.1% | |
| mr._peabody_&_sherman | 1 | 0.1% | |
| pawn_sacrifice | 1 | 0.1% | |
| turbo | 1 | 0.1% | |
| as_above,_so_below | 1 | 0.1% | |
| inherent_vice | 1 | 0.1% | |
| the_east | 1 | 0.1% | |
| need_for_speed | 1 | 0.1% | |
| captain_america:_the_winter_soldier | 1 | 0.1% | |
| Other values (712) | 712 | 98.5% |
Length
| Max length | 59 |
|---|---|
| Median length | 13 |
| Mean length | 14.57952974 |
| Min length | 2 |
| Distinct count | 98 |
|---|---|
| Unique (%) | 14.7% |
| Missing | 58 |
| Missing (%) | 8.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 57.83609022556391 |
|---|---|
| Minimum | 0.0 |
| Maximum | 100.0 |
| Zeros | 4 |
| Zeros (%) | 0.6% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 12 |
| Q1 | 34 |
| median | 61 |
| Q3 | 83 |
| 95-th percentile | 95 |
| Maximum | 100 |
| Range | 100 |
| Interquartile range (IQR) | 49 |
Descriptive statistics
| Standard deviation | 27.50222154 |
|---|---|
| Coefficient of variation (CV) | 0.4755200677 |
| Kurtosis | -1.158299338 |
| Mean | 57.83609023 |
| Median Absolute Deviation (MAD) | 23 |
| Skewness | -0.2979229512 |
| Sum | 38461 |
| Variance | 756.3721895 |
| Value | Count | Frequency (%) | |
| 91 | 16 | 2.2% | |
| 92 | 15 | 2.1% | |
| 84 | 13 | 1.8% | |
| 72 | 13 | 1.8% | |
| 47 | 13 | 1.8% | |
| 18 | 12 | 1.7% | |
| 89 | 12 | 1.7% | |
| 54 | 11 | 1.5% | |
| 81 | 11 | 1.5% | |
| 95 | 11 | 1.5% | |
| Other values (88) | 538 | 74.4% | |
| (Missing) | 58 | 8.0% |
| Value | Count | Frequency (%) | |
| 0 | 4 | 0.6% | |
| 3 | 1 | 0.1% | |
| 4 | 3 | 0.4% | |
| 5 | 2 | 0.3% | |
| 7 | 6 | 0.8% |
| Value | Count | Frequency (%) | |
| 100 | 2 | 0.3% | |
| 99 | 3 | 0.4% | |
| 98 | 5 | 0.7% | |
| 97 | 9 | 1.2% | |
| 96 | 7 | 1.0% |
| Distinct count | 77 |
|---|---|
| Unique (%) | 11.6% |
| Missing | 58 |
| Missing (%) | 8.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 59.19849624060151 |
|---|---|
| Minimum | 15.0 |
| Maximum | 94.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 15 |
|---|---|
| 5-th percentile | 30 |
| Q1 | 45 |
| median | 59 |
| Q3 | 74 |
| 95-th percentile | 88 |
| Maximum | 94 |
| Range | 79 |
| Interquartile range (IQR) | 29 |
Descriptive statistics
| Standard deviation | 18.05938157 |
|---|---|
| Coefficient of variation (CV) | 0.3050648702 |
| Kurtosis | -0.9046208248 |
| Mean | 59.19849624 |
| Median Absolute Deviation (MAD) | 14 |
| Skewness | -0.03989315974 |
| Sum | 39367 |
| Variance | 326.1412628 |
| Value | Count | Frequency (%) | |
| 49 | 19 | 2.6% | |
| 51 | 17 | 2.4% | |
| 71 | 15 | 2.1% | |
| 44 | 15 | 2.1% | |
| 57 | 15 | 2.1% | |
| 40 | 15 | 2.1% | |
| 38 | 15 | 2.1% | |
| 76 | 15 | 2.1% | |
| 52 | 14 | 1.9% | |
| 41 | 14 | 1.9% | |
| Other values (67) | 511 | 70.7% | |
| (Missing) | 58 | 8.0% |
| Value | Count | Frequency (%) | |
| 15 | 1 | 0.1% | |
| 17 | 1 | 0.1% | |
| 19 | 1 | 0.1% | |
| 20 | 1 | 0.1% | |
| 22 | 2 | 0.3% |
| Value | Count | Frequency (%) | |
| 94 | 2 | 0.3% | |
| 93 | 3 | 0.4% | |
| 92 | 4 | 0.6% | |
| 91 | 9 | 1.2% | |
| 90 | 4 | 0.6% |
| Distinct count | 661 |
|---|---|
| Unique (%) | 92.1% |
| Missing | 5 |
| Missing (%) | 0.7% |
| Memory size | 5.6 KiB |
| Sin Datos | 56 |
|---|---|
| a fateful blow to the head makes a middle aged lesbian housewife robin weigert seek satisfaction as a high end escort | 2 |
| a drug addled manipulative misanthrope james mcavoy begins to experience increasingly severe hallucinations as he tries to solve the murder of a japanese student | 2 |
| hoping to harness the magical smurf essence evil wizard gargamel creates a pair of smurflike creatures called naughties however only a real smurf can give gargamel what he wants so he kidnaps smurfette to force her to cast a spell that will transform the naughties into smurfs papa clumsy and the rest of the smurfs reunite with their human friends patrick neil patrick harris and grace jayma mays to rescue smurfette from the wizard s clutches | 1 |
| looking for an exciting career young bobby dorfman leaves new york for the glitz and glamour of 1930s hollywood after landing a job with his uncle bobby falls for vonnie a charming woman who happens to be his employer s mistress settling for friendship but ultimately heartbroken bobby returns to the bronx and begins working in a nightclub everything falls into place when he finds romance with a beautiful socialite until vonnie walks back into his life and captures his heart once again | 1 |
| Other values (656) |
| Value | Count | Frequency (%) | |
| Sin Datos | 56 | 7.7% | |
| a fateful blow to the head makes a middle aged lesbian housewife robin weigert seek satisfaction as a high end escort | 2 | 0.3% | |
| a drug addled manipulative misanthrope james mcavoy begins to experience increasingly severe hallucinations as he tries to solve the murder of a japanese student | 2 | 0.3% | |
| hoping to harness the magical smurf essence evil wizard gargamel creates a pair of smurflike creatures called naughties however only a real smurf can give gargamel what he wants so he kidnaps smurfette to force her to cast a spell that will transform the naughties into smurfs papa clumsy and the rest of the smurfs reunite with their human friends patrick neil patrick harris and grace jayma mays to rescue smurfette from the wizard s clutches | 1 | 0.1% | |
| looking for an exciting career young bobby dorfman leaves new york for the glitz and glamour of 1930s hollywood after landing a job with his uncle bobby falls for vonnie a charming woman who happens to be his employer s mistress settling for friendship but ultimately heartbroken bobby returns to the bronx and begins working in a nightclub everything falls into place when he finds romance with a beautiful socialite until vonnie walks back into his life and captures his heart once again | 1 | 0.1% | |
| anna is a bereft young german woman whose fiance frantz was killed in the trenches of world war i adrien a french veteran of the war makes a mysterious appearance in her town placing flowers on frantz s grave adrien s presence is met with resistance by the small community still reeling from germany s defeat yet anna gradually becomes closer to the handsome and melancholy young man as she learns of his deep friendship with frantz | 1 | 0.1% | |
| mild mannered sheep farmer albert stark seth macfarlane feels certain that the western frontier is trying to kill him then he loses his girlfriend louise amanda seyfried to the town s most successful businessman however a beautiful pistol packing woman named anna charlize theron rides into town and helps albert find his inner courage then stark must put his newfound bravery to the test when anna s outlaw husband arrives with plans to plant him in an unmarked grave | 1 | 0.1% | |
| in rural england 1865 a woman who is trapped in a loveless marriage to a much older man begins a passionate affair with a man her own age | 1 | 0.1% | |
| in the years before the civil war solomon northup chiwetel ejiofor a free black man from upstate new york is kidnapped and sold into slavery in the south subjected to the cruelty of one malevolent owner michael fassbender he also finds unexpected kindness from another as he struggles continually to survive and maintain some of his dignity then in the 12th year of the disheartening ordeal a chance meeting with an abolitionist from canada changes solomon s life forever | 1 | 0.1% | |
| when astronauts blast off from the planet mars they leave behind mark watney matt damon presumed dead after a fierce storm with only a meager amount of supplies the stranded visitor must utilize his wits and spirit to find a way to survive on the hostile planet meanwhile back on earth members of nasa and a team of international scientists work tirelessly to bring him home while his crew mates hatch their own plan for a daring rescue mission | 1 | 0.1% | |
| Other values (651) | 651 | 90.0% | |
| (Missing) | 5 | 0.7% |
Length
| Max length | 499 |
|---|---|
| Median length | 466 |
| Mean length | 354.2655602 |
| Min length | 3 |
ruta
URL
| Distinct count | 721 |
|---|---|
| Unique (%) | 99.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 5.6 KiB |
| https://www.rottentomatoes.com/m/concussion | 2 |
|---|---|
| https://www.rottentomatoes.com/m/filth_2013 | 2 |
| https://www.rottentomatoes.com/m/kill_the_messenger_2015 | 1 |
| https://www.rottentomatoes.com/m/eye_in_the_sky | 1 |
| https://www.rottentomatoes.com/m/big_hero_6 | 1 |
| Other values (716) |
| Value | Count | Frequency (%) | |
| https://www.rottentomatoes.com/m/concussion | 2 | 0.3% | |
| https://www.rottentomatoes.com/m/filth_2013 | 2 | 0.3% | |
| https://www.rottentomatoes.com/m/kill_the_messenger_2015 | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/eye_in_the_sky | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/big_hero_6 | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/nocturnal_animals | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/nebraska | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/x_men_apocalypse | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/irrational_man | 1 | 0.1% | |
| https://www.rottentomatoes.com/m/august_osage_county | 1 | 0.1% | |
| Other values (711) | 711 | 98.3% |
| Value | Count | Frequency (%) | |
| https | 723 | 100.0% |
| Value | Count | Frequency (%) | |
| www.rottentomatoes.com | 723 | 100.0% |
| Value | Count | Frequency (%) | |
| /m/concussion | 2 | 0.3% | |
| /m/filth_2013 | 2 | 0.3% | |
| /m/philomena | 1 | 0.1% | |
| /m/gangster_squad_2012 | 1 | 0.1% | |
| /m/carol | 1 | 0.1% | |
| /m/life_after_beth | 1 | 0.1% | |
| /m/transcendence_2014 | 1 | 0.1% | |
| /m/i_spit_on_your_grave_2 | 1 | 0.1% | |
| /m/selma | 1 | 0.1% | |
| /m/contracted | 1 | 0.1% | |
| Other values (711) | 711 | 98.3% |
| Value | Count | Frequency (%) | |
| 723 | 100.0% |
| Value | Count | Frequency (%) | |
| 723 | 100.0% |
| Distinct count | 53 |
|---|---|
| Unique (%) | 7.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 18.589211618257263 |
|---|---|
| Minimum | 0 |
| Maximum | 2672 |
| Zeros | 292 |
| Zeros (%) | 40.4% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 1 |
| Q3 | 2 |
| 95-th percentile | 22.6 |
| Maximum | 2672 |
| Range | 2672 |
| Interquartile range (IQR) | 2 |
Descriptive statistics
| Standard deviation | 135.6247624 |
|---|---|
| Coefficient of variation (CV) | 7.295885655 |
| Kurtosis | 225.1033012 |
| Mean | 18.58921162 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | 13.43063868 |
| Sum | 13440 |
| Variance | 18394.07617 |
| Value | Count | Frequency (%) | |
| 0 | 292 | 40.4% | |
| 1 | 223 | 30.8% | |
| 2 | 74 | 10.2% | |
| 3 | 23 | 3.2% | |
| 4 | 19 | 2.6% | |
| 5 | 14 | 1.9% | |
| 7 | 8 | 1.1% | |
| 6 | 7 | 1.0% | |
| 8 | 5 | 0.7% | |
| 9 | 5 | 0.7% | |
| Other values (43) | 53 | 7.3% |
| Value | Count | Frequency (%) | |
| 0 | 292 | 40.4% | |
| 1 | 223 | 30.8% | |
| 2 | 74 | 10.2% | |
| 3 | 23 | 3.2% | |
| 4 | 19 | 2.6% |
| Value | Count | Frequency (%) | |
| 2672 | 1 | 0.1% | |
| 1252 | 1 | 0.1% | |
| 1245 | 1 | 0.1% | |
| 898 | 1 | 0.1% | |
| 618 | 1 | 0.1% |
| Distinct count | 6 |
|---|---|
| Unique (%) | 0.9% |
| Missing | 58 |
| Missing (%) | 8.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2.9037593984962404 |
|---|---|
| Minimum | 0.0 |
| Maximum | 5.0 |
| Zeros | 26 |
| Zeros (%) | 3.6% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 2 |
| median | 3 |
| Q3 | 4 |
| 95-th percentile | 5 |
| Maximum | 5 |
| Range | 5 |
| Interquartile range (IQR) | 2 |
Descriptive statistics
| Standard deviation | 1.422623045 |
|---|---|
| Coefficient of variation (CV) | 0.4899245597 |
| Kurtosis | -1.027528024 |
| Mean | 2.903759398 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | -0.2483756321 |
| Sum | 1931 |
| Variance | 2.023856328 |
| Value | Count | Frequency (%) | |
| 4 | 196 | 27.1% | |
| 2 | 124 | 17.2% | |
| 3 | 120 | 16.6% | |
| 1 | 114 | 15.8% | |
| 5 | 85 | 11.8% | |
| 0 | 26 | 3.6% | |
| (Missing) | 58 | 8.0% |
| Value | Count | Frequency (%) | |
| 0 | 26 | 3.6% | |
| 1 | 114 | 15.8% | |
| 2 | 124 | 17.2% | |
| 3 | 120 | 16.6% | |
| 4 | 196 | 27.1% |
| Value | Count | Frequency (%) | |
| 5 | 85 | 11.8% | |
| 4 | 196 | 27.1% | |
| 3 | 120 | 16.6% | |
| 2 | 124 | 17.2% | |
| 1 | 114 | 15.8% |
| Distinct count | 5 |
|---|---|
| Unique (%) | 0.8% |
| Missing | 58 |
| Missing (%) | 8.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2.954887218045113 |
|---|---|
| Minimum | 1.0 |
| Maximum | 5.0 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 5.6 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 2 |
| Q1 | 2 |
| median | 3 |
| Q3 | 4 |
| 95-th percentile | 4 |
| Maximum | 5 |
| Range | 4 |
| Interquartile range (IQR) | 2 |
Descriptive statistics
| Standard deviation | 0.9399489032 |
|---|---|
| Coefficient of variation (CV) | 0.318099756 |
| Kurtosis | -0.7480501217 |
| Mean | 2.954887218 |
| Median Absolute Deviation (MAD) | 1 |
| Skewness | -0.05191936713 |
| Sum | 1965 |
| Variance | 0.8835039406 |
| Value | Count | Frequency (%) | |
| 3 | 224 | 31.0% | |
| 2 | 198 | 27.4% | |
| 4 | 194 | 26.8% | |
| 1 | 31 | 4.3% | |
| 5 | 18 | 2.5% | |
| (Missing) | 58 | 8.0% |
| Value | Count | Frequency (%) | |
| 1 | 31 | 4.3% | |
| 2 | 198 | 27.4% | |
| 3 | 224 | 31.0% | |
| 4 | 194 | 26.8% | |
| 5 | 18 | 2.5% |
| Value | Count | Frequency (%) | |
| 5 | 18 | 2.5% | |
| 4 | 194 | 26.8% | |
| 3 | 224 | 31.0% | |
| 2 | 198 | 27.4% | |
| 1 | 31 | 4.3% |
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.First rows
| budget | company | country | director | genre | gross | name | rating | day_released | month_released | year_released | released | runtime | score | star | votes | writer | year | hashtag | name_roten | calificacion1 | calificacion2 | synopsis | ruta | promedio_ganancia | calificacion1_dec | calificacion2_dec | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 100000000 | Red Granite Pictures | USA | Martin Scorsese | Biography | 116900694 | The Wolf of Wall Street | R | 25 | 12 | 2013 | 2013-12-25 | 180 | 8.2 | Leonardo DiCaprio | 895552 | Terence Winter | 2013 | #TheWolfofWallStreet | the_wolf_of_wall_street | 80.0 | 83.0 | in 1987 jordan belfort leonardo dicaprio takes an entry level job at a wall street brokerage firm by the early 1990s while still in his 20s belfort founds his own firm stratton oakmont together with his trusted lieutenant jonah hill and a merry band of brokers belfort makes a huge fortune by defrauding wealthy investors out of millions however while belfort and his cronies partake in a hedonistic brew of sex drugs and thrills the sec and the fbi close in on his empire of excess | https://www.rottentomatoes.com/m/the_wolf_of_wall_street_2013 | 1 | 4.0 | 4.0 |
| 1 | 20000000 | New Line Cinema | USA | James Wan | Horror | 137400141 | The Conjuring | R | 19 | 7 | 2013 | 2013-07-19 | 112 | 7.5 | Patrick Wilson | 342870 | Chad Hayes | 2013 | #TheConjuring | the_conjuring | 86.0 | 83.0 | in 1970 paranormal investigators and demonologists lorraine vera farmiga and ed patrick wilson warren are summoned to the home of carolyn lili taylor and roger ron livingston perron the perrons and their five daughters have recently moved into a secluded farmhouse where a supernatural presence has made itself known though the manifestations are relatively benign at first events soon escalate in horrifying fashion especially after the warrens discover the house s macabre history | https://www.rottentomatoes.com/m/the_conjuring | 0 | 4.0 | 4.0 |
| 2 | 46000000 | Alcon Entertainment | USA | Denis Villeneuve | Crime | 61002302 | Prisoners | R | 20 | 9 | 2013 | 2013-09-20 | 153 | 8.1 | Hugh Jackman | 449489 | Aaron Guzikowski | 2013 | #Prisoners | prisoners | 81.0 | 87.0 | keller dover hugh jackman faces a parent s worst nightmare when his 6 year old daughter anna and her friend go missing the only lead is an old motorhome that had been parked on their street the head of the investigation detective loki jake gyllenhaal arrests the driver paul dano but a lack of evidence forces loki to release his only suspect dover knowing that his daughter s life is at stake decides that he has no choice but to take matters into his own hands | https://www.rottentomatoes.com/m/prisoners_2013 | 1 | 4.0 | 4.0 |
| 3 | 150000000 | Walt Disney Animation Studios | USA | Chris Buck | Animation | 400738009 | Frozen | PG | 27 | 11 | 2013 | 2013-11-27 | 102 | 7.5 | Kristen Bell | 464149 | Jennifer Lee | 2013 | #Frozen | frozen | 56.0 | 57.0 | a performance artist turns his suicide into a work of art by melting ice with his body | https://www.rottentomatoes.com/m/frozen | 0 | 3.0 | 3.0 |
| 4 | 75000000 | Summit Entertainment | USA | Louis Leterrier | Crime | 117723989 | Now You See Me | PG-13 | 31 | 5 | 2013 | 2013-05-31 | 115 | 7.3 | Jesse Eisenberg | 505432 | Ed Solomon | 2013 | #NowYouSeeMe | now_you_see_me | 51.0 | 70.0 | charismatic magician atlas jesse eisenberg leads a team of talented illusionists called the four horsemen atlas and his comrades mesmerize audiences with a pair of amazing magic shows that drain the bank accounts of the corrupt and funnel the money to audience members a federal agent mark ruffalo and an interpol detective m lanie laurent intend to rein in the horsemen before their next caper and they turn to thaddeus morgan freeman a famous debunker for help | https://www.rottentomatoes.com/m/now_you_see_me | 1 | 3.0 | 4.0 |
| 5 | 23000000 | Annapurna Pictures | USA | Spike Jonze | Drama | 25568251 | Her | R | 10 | 1 | 2014 | 2014-01-10 | 126 | 8.0 | Joaquin Phoenix | 404796 | Spike Jonze | 2013 | #Her | her | 95.0 | 82.0 | a sensitive and soulful man earns a living by writing personal letters for other people left heartbroken after his marriage ends theodore joaquin phoenix becomes fascinated with a new operating system which reportedly develops into an intuitive and unique entity in its own right he starts the program and meets samantha scarlett johansson whose bright voice reveals a sensitive playful personality though friends initially the relationship soon deepens into love | https://www.rottentomatoes.com/m/her | 1 | 5.0 | 4.0 |
| 6 | 225000000 | Warner Bros. | USA | Zack Snyder | Action | 291045518 | Man of Steel | PG-13 | 14 | 6 | 2013 | 2013-06-14 | 143 | 7.1 | Henry Cavill | 590734 | David S. Goyer | 2013 | #ManofSteel | man_of_steel | 56.0 | 75.0 | with the imminent destruction of krypton their home planet jor el russell crowe and his wife seek to preserve their race by sending their infant son to earth the child s spacecraft lands at the farm of jonathan kevin costner and martha diane lane kent who name him clark and raise him as their own son though his extraordinary abilities have led to the adult clark henry cavill living on the fringe of society he finds he must become a hero to save those he loves from a dire threat | https://www.rottentomatoes.com/m/superman_man_of_steel | 1 | 3.0 | 4.0 |
| 7 | 37000000 | New Line Cinema | USA | Rawson Marshall Thurber | Comedy | 150394119 | We're the Millers | R | 7 | 8 | 2013 | 2013-08-7 | 110 | 7.0 | Jason Sudeikis | 342500 | Bob Fisher | 2013 | #We'retheMillers | we're_the_millers | 48.0 | 72.0 | small time pot dealer david jason sudeikis learns the hard way that no good deed goes unpunished trying to help some teens he is jumped by thugs and loses his cash and stash now david s in big debt to his supplier and to wipe the slate clean he must go to mexico to pick up the guy s latest shipment to accomplish his mission dave devises a foolproof plan he packs a fake family into a huge rv and heads south of the border for a wild weekend that is sure to end with a bang | https://www.rottentomatoes.com/m/were_the_millers | 0 | 2.0 | 4.0 |
| 8 | 0 | Quat'sous Films | France | Abdellatif Kechiche | Drama | 2199675 | Blue Is the Warmest Color | NC-17 | 14 | 2 | 2014 | 2014-02-14 | 180 | 7.8 | Léa Seydoux | 107119 | Abdellatif Kechiche | 2013 | #BlueIstheWarmestColor | blue_is_the_warmest_color | 89.0 | 85.0 | a french teen ad le exarchopoulos forms a deep emotional and sexual connection with an older art student l a seydoux she met in a lesbian bar | https://www.rottentomatoes.com/m/blue_is_the_warmest_color | 0 | 4.0 | 4.0 |
| 9 | 190000000 | Warner Bros. | USA | Guillermo del Toro | Action | 101802906 | Pacific Rim | PG-13 | 12 | 7 | 2013 | 2013-07-12 | 131 | 7.0 | Idris Elba | 407588 | Travis Beacham | 2013 | #PacificRim | pacific_rim | 72.0 | 77.0 | long ago legions of monstrous creatures called kaiju arose from the sea bringing with them all consuming war to fight the kaiju mankind developed giant robots called jaegers designed to be piloted by two humans locked together in a neural bridge however even the jaegers are not enough to defeat the kaiju and humanity is on the verge of defeat mankind s last hope now lies with a washed up ex pilot charlie hunnam an untested trainee rinko kikuchi and an old obsolete jaeger | https://www.rottentomatoes.com/m/pacific_rim_2013 | 2 | 4.0 | 4.0 |
Last rows
| budget | company | country | director | genre | gross | name | rating | day_released | month_released | year_released | released | runtime | score | star | votes | writer | year | hashtag | name_roten | calificacion1 | calificacion2 | synopsis | ruta | promedio_ganancia | calificacion1_dec | calificacion2_dec | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 713 | 0 | StudioCanal | UK | Susanna White | Crime | 3152725 | Our Kind of Traitor | R | 30 | 9 | 2016 | 2016-09-30 | 108 | 6.2 | Carlos Acosta | 13857 | John le Carré | 2016 | #OurKindofTraitor | our_kind_of_traitor | 72.0 | 50.0 | a money launderer stellan skarsgard for russian gangsters asks a couple vacationing in marrakech morocco to deliver incriminating evidence to an mi6 agent damian lewis | https://www.rottentomatoes.com/m/our_kind_of_traitor | 0 | 4.0 | 2.0 |
| 714 | 8500000 | CBS Films | USA | Steve Carr | Animation | 19985196 | Middle School: The Worst Years of My Life | PG | 7 | 10 | 2016 | 2016-10-7 | 92 | 6.1 | Griffin Gluck | 4556 | Chris Bowman | 2016 | #MiddleSchool:TheWorstYearsofMyLife | middle_school:_the_worst_years_of_my_life | 63.0 | 58.0 | rafe khatchadorian griffin gluck has an epic imagination and a slight problem with authority and these things collide when he transfers to a middle school where students are expected to follow the rules this doesn t sit well with rafe with help from his new friend leo thomas barbusca the mischievous lad concocts schemes to drive his tyrannical principal andy daly crazy while also using his charm and wits to impress a girl isabela moner and battle the bullies | https://www.rottentomatoes.com/m/middle_school_the_worst_years_of_my_life | 0 | 3.0 | 3.0 |
| 715 | 0 | Killer Films | USA | Andrew Neel | Drama | 23020 | Goat | R | 23 | 9 | 2016 | 2016-09-23 | 96 | 5.7 | Ben Schnetzer | 4439 | David Gordon Green | 2016 | #Goat | goat | 79.0 | 44.0 | nineteen year old brad is a new college student and wants desperately to fit in taking a cue from his older brother brett brad decides to pledge a fraternity at first it s all parties and girls but as brad enters into the final stretch of the pledging ritual known as hell week things take a violent humiliating turn what occurs in the name of brotherhood tests both boys and their relationship in brutal ways | https://www.rottentomatoes.com/m/goat_2016 | 0 | 4.0 | 2.0 |
| 716 | 0 | Anna Biller Productions | USA | Anna Biller | Comedy | 228894 | The Love Witch | UNRATED | 10 | 3 | 2017 | 2017-03-10 | 120 | 6.2 | Samantha Robinson | 6054 | Anna Biller | 2016 | #TheLoveWitch | the_love_witch | 95.0 | 61.0 | elaine samantha robinson a beautiful young witch is determined to find a man to love her in her gothic victorian apartment she makes spells and potions then picks up men and seduces them however her spells work too well and she ends up with a string of hapless victims when she at last meets the man of her dreams her desperation to be loved drives her to the brink of insanity and murder | https://www.rottentomatoes.com/m/the_love_witch | 0 | 5.0 | 3.0 |
| 717 | 20000000 | LD Entertainment | USA | Kevin Reynolds | Action | 36874745 | Risen | PG-13 | 19 | 2 | 2016 | 2016-02-19 | 107 | 6.3 | Joseph Fiennes | 19084 | Kevin Reynolds | 2016 | #Risen | risen | 53.0 | 70.0 | roman military tribune clavius joseph fiennes remains set in his ways after serving 25 years in the army he arrives at a crossroad when he s tasked to investigate the mystery of what happened to jesus cliff curtis following the crucifixion accompanied by trusted aide lucius tom felton his quest to disprove rumors of a risen messiah makes him question his own beliefs and spirituality as his journey takes him to places never dreamed of clavius discovers the truth that he s been seeking | https://www.rottentomatoes.com/m/risen_2016 | 1 | 3.0 | 4.0 |
| 718 | 0 | Fox Searchlight Pictures | UK | Mandie Fletcher | Comedy | 4750497 | Absolutely Fabulous: The Movie | R | 22 | 7 | 2016 | 2016-07-22 | 91 | 5.4 | Jennifer Saunders | 9161 | Jennifer Saunders | 2016 | #AbsolutelyFabulous:TheMovie | absolutely_fabulous:_the_movie | 59.0 | 41.0 | publicist edina monsoon and best friend patsy stone are still shopping drinking and clubbing their way around london s trendiest hot spots while attending an elite party they wind up knocking supermodel kate moss into the river thames her untimely demise creates a media firestorm leading the paparazzi to relentlessly pursue the hapless duo seeking refuge the gals flee to the french riviera where they hatch a plan to make their escape permanent and live the high life forever | https://www.rottentomatoes.com/m/absolutely_fabulous_the_movie | 0 | 3.0 | 2.0 |
| 719 | 0 | Siempre Viva Productions | USA | Paul Duddridge | Drama | 28368 | Mothers and Daughters | PG-13 | 6 | 5 | 2016 | 2016-05-6 | 90 | 4.9 | Selma Blair | 1959 | Paige Cameron | 2016 | #MothersandDaughters | mothers_and_daughters | 18.0 | 28.0 | a pregnant photographer selma blair captures motherhood on film while re examining her relationship with her estranged mom | https://www.rottentomatoes.com/m/mothers_and_daughters_2016 | 0 | 1.0 | 1.0 |
| 720 | 3500000 | Warner Bros. Animation | USA | Sam Liu | Animation | 3775000 | Batman: The Killing Joke | R | 25 | 7 | 2016 | 2016-07-25 | 76 | 6.5 | Kevin Conroy | 36333 | Brian Azzarello | 2016 | #Batman:TheKillingJoke | batman:_the_killing_joke | 40.0 | 46.0 | batman kevin conroy must save commissioner gordon ray wise from the joker s mark hamill twisted quest to drive him insane | https://www.rottentomatoes.com/m/batman_the_killing_joke | 1 | 2.0 | 2.0 |
| 721 | 0 | Borderline Presents | USA | Nicolas Pesce | Drama | 25981 | The Eyes of My Mother | R | 2 | 12 | 2016 | 2016-12-2 | 76 | 6.2 | Kika Magalhães | 6947 | Nicolas Pesce | 2016 | #TheEyesofMyMother | the_eyes_of_my_mother | 78.0 | 57.0 | francisca kika magalhaes has been unfazed by death from an early age because her mother formerly a surgeon in portugal imbued her with a thorough understanding of the human anatomy when tragedy shatters her family s idyllic life in the countryside her deep trauma gradually awakens some unique curiosities as she grows up her desire to connect with the world around her takes a distinctly dark form | https://www.rottentomatoes.com/m/the_eyes_of_my_mother | 0 | 4.0 | 3.0 |
| 722 | 0 | Les Productions du Trésor | France | Nicole Garcia | Drama | 37757 | From the Land of the Moon | R | 28 | 7 | 2017 | 2017-07-28 | 120 | 6.7 | Marion Cotillard | 2411 | Milena Agus | 2016 | #FromtheLandoftheMoon | from_the_land_of_the_moon | 32.0 | 65.0 | after world war ii a free spirited woman marion cotillard in a loveless marriage falls in love with another man | https://www.rottentomatoes.com/m/from_the_land_of_the_moon | 0 | 2.0 | 3.0 |